Electrical cost savings and clean energy usage potential for HPC workloads

被引:0
|
作者
Aikema, David [1 ]
Simmonds, Rob [1 ]
机构
[1] Univ Calgary, Dept Comp Sci, Calgary, AB T2N 1N4, Canada
关键词
Environmental Economics; Adaptive Scheduling; High performance computing; Simulation;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Data centres containing high-performance computing (HPC) clusters may be able to coordinate with the operation of wind farms for mutual benefit. Large data centres consume megawatts of power, typically accounting for a majority of life cycle carbon emissions and a significant portion of the total cost of ownership. We ran simulations to explore the potential for data centres to adapt to dynamic electrical prices, variation in carbon intensity within an electrical grid, or the availability of local renewables. Using workloads from the Parallel Workloads Archive alongside real-world pricing data, we demonstrate potential savings on the cost of electricity ranging typically between 10-50%. Adaptation to the variation in the electrical grid carbon intensity was not as successful, but adaptation to the availability of local renewables showed potential to significantly increase their use. In one example the fraction of power obtained from a local wind installation increased by 10-80%.
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页数:6
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